The COVID-19 outbreak, which emerged in China and continues to spread rapidly all over the world, has brought with it increasing numbers of cases and deaths. Governments have suffered serious damage and losses not only in the field of health but also in many other fields. This has directed governments to adopt and implement various strategies in their communities. However, only a few countries succeed partially from the strategies implemented while other countries have failed. In this context, it is necessary to identify the most important strategy that should be implemented by governments. A decision problem based on the decisions of many experts, with some contradictory and multiple criteria, should be taken into account in order to evaluate the multiple strategies implemented by various governments. In this study, this decision process is considered as a multi-criteria decision making (MCDM) problem that also takes into account uncertainty. For this purpose, q-rung orthopair fuzzy sets (q-ROFSs) are used to allow decision-makers to their assessments in a wider space and to better deal with ambiguous information. Accordingly, two different Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches are recommended under the q-ROFS environment and applied to determine the most appropriate strategy. The results of the proposed approaches determine the A1- Mandatory quarantine and strict isolation strategy as the best strategy. Comparisons with other q-rung orthopair fuzzy MCDM methods and intuitionistic fuzzy TOPSIS method are also presented for the validation of the proposed methods. Besides, sensitivity analyzes are conducted to check the robustness of the proposed approaches and to observe the effect of the change in the q parameter.

A circular intuitionistic fuzzy set (CIFS) recently introduced by Atanassov as a new extension of intuitionistic fuzzy sets is represented by a circle whose radius is r and whose center is composed of membership and non-membership degrees. The idea is similar to type-2 fuzzy sets, which are based on the fuzziness of membership functions with a third dimension. CIFSs help us define membership functions more flexibly, taking into account the vagueness in membership and non-membership degrees. In this study, TOPSIS, which is a multi-criteria decision-making (MCDM) method, is developed under circular intuitionistic fuzzy environment. The proposed CIF-TOPSIS method is applied to determine the most appropriate pandemic hospital location selection problem. Then, a sensitivity analysis based on criteria weights and the weight of the decision maker’s optimistic and pessimistic attitudes are conducted to check the robustness of the decisions given by the proposed approach. A comparative analysis with the single-valued intuitionistic fuzzy TOPSIS, Pythagorean fuzzy TOPSIS, picture fuzzy TOPSIS methods is also performed to verify the developed approach and to demonstrate its effectiveness.

The membership function of a general type-2 fuzzy set is three-dimensional in order to incorporate its vagueness through the third dimension. Similarly, Circular intuitionistic fuzzy sets (CIFSs) have been recently introduced by Atanassov (2020) as a new extension of intuitionistic fuzzy sets, which are represented by a circle representing the vagueness of the membership function. CIFSs allow decision-makers to express their judgments including this vagueness. In this study, the TOPSIS method, which is one of the most used multi-criteria decision-making methods is extended to its CIF version. The proposed CIF-TOPSIS methodology is applied to the supplier selection problem. Then, a sensitivity analysis based on criteria weights is conducted to check the robustness of the proposed approach. A comparative analysis with single-valued intuitionistic fuzzy TOPSIS method is also performed to verify the developed approach and to demonstrate its effectiveness

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Innovations in technology emerged with digitalization affect all sectors, including supply chain and logistics. The term “digital supply chain” has arisen as a relatively new concept in the manufacturing and service sectors. Organizations planning to utilize the benefits of digitalization, especially in the supply chain area, have uncertainties on how to adapt digitalization, which criteria they will evaluate, what kind of strategies should be developed, and which should be given more importance. Multi-criteria decision making (MCDM) approaches can be addressed to determine the best strategy under various criteria in digital transformation. Because of the need to capture this uncertainty, fermatean fuzzy sets (FFSs) have been preferred in the study to widen the definition domain of uncertainty parameters. Interval-valued fermatean fuzzy sets (IVFFSs) are one of the most often used fuzzy set extensions to cope with uncertainty. Therefore, a new interval-valued fermatean fuzzy analytic hierarchy process (IVFF-AHP) method has been developed. After determining the main criteria and sub-criteria, the IVFF-AHP method has been used for calculating the criteria weights and ranking the alternatives. By determining the most important strategy and criteria, the study provides a comprehensive framework of digital transformation in the supply chain.